Human Nutrition Research in the Data Era: Results of 11 Reports on the Effects of a Multiple-Micronutrient-Intervention Study

Large datasets have been used in molecular and genetic research for decades, but only a few studies have included nutrition and lifestyle factors. Our team conducted an n-of-1 intervention with 12 vitamins and five minerals in 9- to 13-year-old Brazilian children and teens with poor healthy-eating indices. A unique feature of the experimental design was the inclusion of a replication arm. Twenty-six types of data were acquired including clinical measures, whole-genome mapping, whole-exome sequencing, and proteomic and a variety of metabolomic measurements over two years. A goal of this study was to use these diverse data sets to discover previously undetected physiological effects associated with a poor diet that include a more complete micronutrient composition. We summarize the key findings of 11 reports from this study that (i) found that LDL and total cholesterol and fasting glucose decreased in the population after the intervention but with inter-individual variation; (ii) associated a polygenic risk score that predicted baseline vitamin B12 levels; (iii) identified metabotypes linking diet intake, genetic makeup, and metabolic physiology; (iv) found multiple biomarkers for nutrient and food groups; and (v) discovered metabolites and proteins that are associated with DNA damage. This summary also highlights the limitations and lessons in analyzing diverse omic data.

Identifying and Analyzing Topic Clusters in a Nutri-, Food-, and Diet-Proteomic Corpus Using Machine Reading

Nutrition affects the early stages of disease development, but the mechanisms remain poorly understood. High-throughput proteomic methods are being used to generate data and information on the effects of nutrients, foods, and diets on health and disease processes. In this report, a novel machine reading pipeline was used to identify all articles and abstracts on proteomics, diet, food, and nutrition in humans. The resulting proteomic corpus was further analyzed to produce seven clusters of "thematic" content defined as documents that have similar word content. Examples of publications from several of these clusters were then described in a similar way to a typical descriptive review.

DNA Damage, n-3 Long-Chain PUFA Levels and Proteomic Profile in Brazilian Children and Adolescents

Fatty acids play a significant role in maintaining cellular and DNA protection and we previously found an inverse relationship between blood levels of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) and DNA damage. The aim of this study was to explore differences in proteomic profiles, for 117 pro-inflammatory proteins, in two previously defined groups of individuals with different DNA damage and EPA and DHA levels. Healthy children and adolescents (n = 140) aged 9 to 13 years old in an urban area of Brazil were divided by k-means cluster test into two clusters of DNA damage (tail intensity) using the comet assay (cluster 1 = 5.9% ± 1.2 and cluster 2 = 13.8% ± 3.1) in our previous study. The cluster with higher DNA damage and lower levels of DHA (6.2 ± 1.6 mg/dL; 5.4 ± 1.3 mg/dL, p = 0.003) and EPA (0.6 ± 0.2 mg/dL; 0.5 ± 0.1 mg/dL, p < 0.001) presented increased expression of the proteins CDK8-CCNC, PIK3CA-PIK3R1, KYNU, and PRKCB, which are involved in pro-inflammatory pathways. Our findings support the hypothesis that low levels of n-3 long-chain PUFA may have a less protective role against DNA damage through expression of pro-inflammatory proteins, such as CDK8-CCNC, PIK3CA-PIK3R1, KYNU, and PRKCB.

Contribution of genetic ancestry and polygenic risk score in meeting vitamin B12 needs in healthy Brazilian children and adolescents

Polymorphisms in genes related to the metabolism of vitamin B12 haven’t been examined in a Brazilian population. To (a) determine the correlation between the local genetic ancestry components and vitamin B12 levels using ninety B12-related genes; (b) determine associations between these genes and their SNPs with vitamin B12 levels; (c) determine a polygenic risk score (PRS) using significant variants. This cross-sectional study included 168 children and adolescents, aged 9–13 years old. Total cobalamin was measured in plasma. Genotyping arrays and whole exome data were combined to yield ~ 7000 SNPs in 90 genes related to vitamin B12. The Efficient Local Ancestry Inference was used to estimate local ancestry for African (AFR), Native American, and European (EUR). The association between the genotypes and vitamin B12 levels were determined with generalized estimating equation. Vitamin B12 levels were driven by positive (EUR) and negative (AFR, AMR) correlations with genetic ancestry. A set of 36 variants were used to create a PRS that explained 42% of vitamin level variation. Vitamin B12 levels are influenced by genetic ancestry and a PRS explained almost 50% of the variation in plasma cobalamin in Brazilian children and adolescents.

DNA damage is inversely associated to blood levels of DHA and EPA fatty acids in Brazilian children and adolescents

This study aimed to investigate the association between DNA damage and blood levels of docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), retinol, beta-carotene and riboflavin in Brazilian children and adolescents. Subjects (n = 140) were healthy boys and girls aged 9 to 13 years in Ribeirão Preto (SP, Brazil). Data collection included anthropometry, assessment of energy intake and blood sampling. DNA damage was evaluated by single-cell gel electrophoresis (comet assay). Principal component analysis (PCA) was used to verify associations between blood concentrations of vitamins, polyunsaturated fatty acids and DNA damage. Multiple regression analyses, k-means cluster, and analysis of covariance (ANCOVA), adjusted for confounding variables such as age, sex, energy intake, body mass index and total cholesterol (when needed), were applied to confirm the associations. PCA explained 69.4% of the inverse relationships between DNA damage and blood levels of DHA, EPA, retinol, and beta-carotene. Results were confirmed by ANCOVA and multiple regression analyses for DHA and EPA. In conclusion, omega-3-fatty acids were inversely associated with DNA damage in Brazilian children and adolescents and may be a protective factor against the development of future diseases.

Metabolic Groups Related to Blood Vitamin Levels and Inflammatory Biomarkers in Brazilian Children and Adolescents

Certain B-vitamins and vitamin A may be involved in inflammatory pathways associated with homocysteine and omega-3 fatty acids. The aims of this study were (i) to determine whether different metabolic profiles of B-vitamins and vitamin A in Brazilian children and adolescents were positively or negatively related to homocysteine and omega-3 fatty acids using k-means clustering analysis, (ii) compare nutrient intakes and metabolites between the different metabolic profiles, (iii) evaluate if the statistically significant metabolites found between the metabolic groups, can predict the variation of leukotriene A4 hydrolase (LTA4H) levels, a biomarker of low-grade inflammation, in the total studied population. This cross-sectional study included 124 children and adolescents, aged 9-13 y old. Dietary intake was assessed by the food frequency questionnaire and 24-hour recall. Biomarkers for vitamins B2, B6, B12, folate and vitamin A were measured in plasma. Omega-3 fatty acids and homocysteine were measured in red blood cells (RBC). Two different metabolic profiles were found. Thirty of these individuals had overall average higher riboflavin, pyridoxal, and vitamin B12 plasma levels (metabolic group 1) compared to 94 individuals (group 2). Group 2 had lower dietary intake of vitamin B2, vitamin A, and vitamin B12 and higher RBC levels of homocysteine. EPA and DHA erythrocyte levels were not different between metabolic groups. Multiple linear regression analyses showed that blood cobalamin, riboflavin, pyridoxal and homocysteine combined, explained 9.0% of LTA4H levels variation in the total studied population. The metabolic group that had low plasma levels of riboflavin, pyridoxal, and cobalamin also had a lower dietary intake of B-vitamin and higher RBC homocysteine. The combined levels of the riboflavin, pyridoxal, cobalamin and homocysteine biomarkers can predict the variation of LTA4H in the total population studied, but it is not clear how this regulation occurs.

DNA methylation during human adipogenesis and the impact of fructose

BACKGROUND

Increased adipogenesis and altered adipocyte function contribute to the development of obesity and associated comorbidities. Fructose modified adipocyte metabolism compared to glucose, but the regulatory mechanisms and consequences for obesity are unknown. Genome-wide methylation and global transcriptomics in SGBS pre-adipocytes exposed to 0, 2.5, 5, and 10 mM fructose, added to a 5-mM glucose-containing medium, were analyzed at 0, 24, 48, 96, 192, and 384 h following the induction of adipogenesis.

RESULTS

Time-dependent changes in DNA methylation compared to baseline (0 h) occurred during the final maturation of adipocytes, between 192 and 384 h. Larger percentages (0.1% at 192 h, 3.2% at 384 h) of differentially methylated regions (DMRs) were found in adipocytes differentiated in the glucose-containing control media compared to adipocytes differentiated in fructose-supplemented media (0.0006% for 10 mM, 0.001% for 5 mM, and 0.005% for 2.5 mM at 384 h). A total of 1437 DMRs were identified in 5237 differentially expressed genes at 384 h post-induction in glucose-containing (5 mM) control media. The majority of them inversely correlated with the gene expression, but 666 regions were positively correlated to the gene expression.

CONCLUSIONS

Our studies demonstrate that DNA methylation regulates or marks the transformation of morphologically differentiating adipocytes (seen at 192 h), to the more mature and metabolically robust adipocytes (as seen at 384 h) in a genome-wide manner. Lower (2.5 mM) concentrations of fructose have the most robust effects on methylation compared to higher concentrations (5 and 10 mM), suggesting that fructose may be playing a signaling/regulatory role at lower concentrations of fructose and as a substrate at higher concentrations.

Biomarker-based validity of a food frequency questionnaire estimating intake in Brazilian children and adolescents

This study evaluated the validity of nutrient and food group intakes estimated by an FFQ against biomarkers. A 71-item semiquantitative FFQ was administered to 210 Brazilian children and adolescents aged 9-13 years. Intakes were correlated with biomarkers in plasma and red blood cells. Correlations between nutrients and their biomarkers were presented for animal protein, myristic acid (C14:0), EPA, DHA, β-carotene, folate, and vitamins B3, B5 and B6. Food groups and biomarkers were correlated as follows: fish products with EPA and DHA; milk and dairy with C14:0, pyridoxal 5'-phosphate and vitamin B12; total vegetables and dark green and orange vegetables with β-carotene; 5-methyltetrahydrofolate with green vegetables; and flour products with para-aminobenzoylglutamic acid. This FFQ is a valid tool for ranking Brazilian children and adolescents according to their intake of several nutrients and food groups.

Metabo groups in response to micronutrient intervention: Pilot study

Micronutrients and their metabolites are cofactors in proteins involved in lipid metabolism. The present study was a subproject of the Harmonized Micronutrient Project (ClinTrials.gov # NCT01823744). Twenty participants were randomly selected from 136 children and adolescents that consumed a daily dose of 12 vitamins and 5 minerals supplementation for 6 weeks. The 20 individuals were divided into two pools of 10 individuals, according to their lipid profile at baseline (Pool 1 with lower triglycerides, LDL, and VLDL). The individuals were analyzed at baseline, after 6 weeks of daily supplementation, and after 6 weeks of a washout period in relation to anthropometric, body composition, food intake, lipid profile, micronutrient levels, and iTRAQ proteomic data. Genetic ancestry and its association with vitamin serum levels were also determined. After supplementation, LDL levels decreased while alpha-tocopherol and pantothenic acid levels increased in pool 2; lipid profiles in pool 1 did not change but had higher plasma levels of pantothenic acid, pyridoxal, and pyridoxic acid. In pool 2, expression of some proteins increased, and expression of other ones decreased after intervention, while in pool 1, the same proteins responded inversely or did not change their levels. Plasma alpha-tocopherol and Native American genetic ancestry explained a significant fraction of LDL plasma levels at baseline and in response to the intervention. After intervention, changes in expression of alpha-1 antitrypsin, haptoglobin, Ig alpha-1 chain C region, plasma protease C1 inhibitor, alpha-1-acid glycoprotein 1, fibrinogen alpha, beta, and gamma-chain in individuals in pool 2 may be associated with levels of LDL and vitamin E. Vitamin E and Native American genetic ancestry may also be implicated in changes of vitamin E and LDL levels. The results of this pilot study must be validated in future studies with larger sample size or in in vitro studies.

Targeting the delivery of dietary plant bioactives to those who would benefit most: from science to practical applications

Background

A healthy diet and optimal lifestyle choices are amongst the most important actions for the prevention of cardiometabolic diseases. Despite this, it appears difficult to convince consumers to select more nutritious foods. Furthermore, the development and production of healthier foods do not always lead to economic profits for the agro-food sector. Most dietary recommendations for the general population represent a “one-size-fits-all approach” which does not necessarily ensure that everyone has adequate exposure to health-promoting constituents of foods. Indeed, we now know that individuals show a high variability in responses when exposed to specific nutrients, foods, or diets.

Purpose

This review aims to highlight our current understanding of inter-individual variability in response to dietary bioactives, based on the integration of findings of the COST Action POSITIVe. We also evaluate opportunities for translation of scientific knowledge on inter-individual variability in response to dietary bioactives, once it becomes available, into practical applications for stakeholders, such as the agro-food industry. The potential impact from such applications will form an important impetus for the food industry to develop and market new high quality and healthy foods for specific groups of consumers in the future. This may contribute to a decrease in the burden of diet-related chronic diseases.

Individual differences in ADME (Absorption, Digestion, Metabolism and Excretion) is believed to underpin much of the inter-individual variation in responses.

Recent developments in the area of food metabolome databases and fast improvements in innovative metabotyping technologies hold great promise for improved profiling of dietary intake, exposure to individual ingredients, foods and dietary patterns, as well as our ability to identify individual responsiveness.

The food industry needs well-defined population clusters or targets in order to be able to design “personalized products”.

There are indeed excellent industrial opportunities for foods that modulate gut microbiota, and thereby enable the delivery of food bioactive metabolites.

It is currently not clear whether knowledge on individual nutrient needs, based on genetic or metagenomic data, would affect long-term dietary and health behaviours.

Data to support the development of dietary recommendations may need to be generated by new n-of-1-based study designs in the future.

Impact of multi-micronutrient supplementation on lipidemia of children and adolescents

BACKGROUND

Micronutrient supplementation has been extensively explored as a strategy to improve health and reduce risk of chronic diseases. Fat-soluble vitamins like A and E with their antioxidant properties and mechanistic interactions with lipoproteins, have potentially a key impact on lipid metabolism and lipidemia.

OBJECTIVE

The impact of micronutrients on lipid metabolism requires further investigation including characterization of plasma lipidome following supplementation and any cause-effect on circulating lipids.

DESIGN

In this study, we elucidate the effect and associations of a multi-micronutrient intervention in Brazilian children and teens with lipoprotein alterations and lipid metabolism.

RESULTS

Our analysis suggests a combination of short and long-term impact of supplementation on lipid metabolism, potentially mediated primarily by α-tocopherol (vitamin E) and retinol (vitamin A). Among the lipid classes, levels of phospholipids, lysophospholipids, and cholesterol esters were impacted the most along with differential incorporation of stearic, palmitic, oleic and arachidonic acids. Integrated analysis with proteomic data suggested potential links to supplementation-mediated alterations in protein levels of phospholipases and pyruvate dehydrogenase kinase 1 (PDK1).

CONCLUSIONS

Associations between the observed differences in lipidemia, total triglyceride, and VLDL-cholesterol levels suggest that micronutrients may play a role in reducing these risk factors for cardiovascular disease in children. This would require further investigation.

A proteomic signature that reflects pancreatic beta-cell function

AIM

Proteomics has the potential to enhance early identification of beta-cell dysfunction, in conjunction with monitoring the various stages of type 2 diabetes onset. The most routine method of assessing pancreatic beta-cell function is an oral glucose tolerance test, however this method is time consuming and carries a participant burden. The objectives of this research were to identify protein signatures and pathways related to pancreatic beta-cell function in fasting blood samples.

METHODS

Beta-cell function measures were calculated for MECHE study participants who completed an oral glucose tolerance test and had proteomic data (n = 100). Information on 1,129 protein levels was obtained using the SOMAscan assay. Receiver operating characteristic curves were used to assess discriminatory ability of proteins of interest. Subsequent in vitro experiments were performed using the BRIN-BD11 pancreatic beta-cell line. Replication of findings were achieved in a second human cohort where possible.

RESULTS

Twenty-two proteins measured by aptamer technology were significantly associated with beta-cell function/HOMA-IR while 17 proteins were significantly associated with the disposition index (p ≤ 0.01). Receiver operator characteristic curves determined the protein panels to have excellent discrimination between low and high beta-cell function. Linear regression analysis determined that beta-endorphin and IL-17F have strong associations with beta-cell function/HOMA-IR, β = 0.039 (p = 0.005) and β = -0.027 (p = 0.013) respectively. Calcineurin and CRTAM were strongly associated with the disposition index (β = 0.005 and β = 0.005 respectively, p = 0.012). In vitro experiments confirmed that IL-17F modulated insulin secretion in the BRIN-BD11 cell line, with the lower concentration of 10 ng/mL significantly increasing glucose stimulated insulin secretion (p = 0.043).

CONCLUSIONS

Early detection of compromised beta-cell function could allow for implementation of nutritional and lifestyle interventions before progression to type 2 diabetes.

Clinical and Vitamin Response to a Short-Term Multi-Micronutrient Intervention in Brazilian Children and Teens: From Population Data to Interindividual Responses

SCOPE

Micronutrients are in small amounts in foods, act in concert, and require variable amounts of time to see changes in health and risk for disease. These first principles are incorporated into an intervention study designed to develop new experimental strategies for setting target recommendations for food bioactives for populations and individuals.

METHODS AND RESULTS

A 6-week multivitamin/mineral intervention is conducted in 9-13 year olds. Participants (136) are (i) their own control (n-of-1); (ii) monitored for compliance; (iii) measured for 36 circulating vitamin forms, 30 clinical, anthropometric, and food intake parameters at baseline, post intervention, and following a 6-week washout; and (iv) had their ancestry accounted for as modifier of vitamin baseline or response. The same intervention is repeated the following year (135 participants). Most vitamins respond positively and many clinical parameters change in directions consistent with improved metabolic health to the intervention. Baseline levels of any metabolite predict its own response to the intervention. Elastic net penalized regression models are identified, and significantly predict response to intervention on the basis of multiple vitamin/clinical baseline measures.

CONCLUSIONS

The study design, computational methods, and results are a step toward developing recommendations for optimizing vitamin levels and health parameters for individuals.

A computationally driven analysis of the polyphenol-protein interactome

Polyphenol-rich foods are part of many nutritional interventions aimed at improving health and preventing cardiometabolic diseases (CMDs). Polyphenols have oxidative, inflammatory, and/or metabolic effects. Research into the chemistry and biology of polyphenol bioactives is prolific but knowledge of their molecular interactions with proteins is limited. We mined public data to (i) identify proteins that interact with or metabolize polyphenols, (ii) mapped these proteins to pathways and networks, and (iii) annotated functions enriched within the resulting polyphenol-protein interactome. A total of 1,395 polyphenols and their metabolites were retrieved (using Phenol-Explorer and Dictionary of Natural Products) of which 369 polyphenols interacted with 5,699 unique proteins in 11,987 interactions as annotated in STITCH, Pathway Commons, and BindingDB. Pathway enrichment analysis using the KEGG repository identified a broad coverage of significant pathways of low specificity to particular polyphenol (sub)classes. When compared to drugs or micronutrients, polyphenols have pleiotropic effects across many biological processes related to metabolism and CMDs. These systems-wide effects were also found in the protein interactome of the polyphenol-rich citrus fruits, used as a case study. In sum, these findings provide a knowledgebase for identifying polyphenol classes (and polyphenol-rich foods) that individually or in combination influence metabolism.

Validation of the Brazilian Healthy Eating Index-Revised Using Biomarkers in Children and Adolescents

The Brazilian Healthy Eating Index-Revised (BHEI-R) can be used to determine overall dietary patterns. We assessed the BHEI-R scores in children and adolescents, aged from 9 to 13 years old, and associated its component scores with biomarkers of health and dietary exposure. Three 24-h recalls were used to generate BHEI-R. Biomarkers were analyzed in plasma and red blood cells. Correlation tests, agreement, and covariance analyses were used to associate BHEI-R components with biomarkers. Data from 167 subjects were used. The strongest correlations were between fruits, vegetables and legumes with omega-6 and omega-3 fatty acids, and β-carotene intakes. Milk and dairy correlated with plasma retinol and pyridoxine. All components rich in vegetable and animal protein sources correlated with plasma creatine. Total BHEI-R scores were positively associated with intakes of omega-6, omega-3, fiber and vitamin C, and inversely associated with energy and saturated fat intakes of individuals. Plasma β-carotene and riboflavin biomarkers were positively associated with total BHEI-R. An inadequate food consumption pattern was captured by both biomarkers of health and dietary exposure. BHEI-R was validated for the above dietary components and can be associated with metabolomics and nutritional epidemiological data in future pediatric studies.

A 48-Hour Vegan Diet Challenge in Healthy Women and Men Induces a BRANCH-Chain Amino Acid Related, Health Associated, Metabolic Signature

SCOPE

Research is limited on diet challenges to improve health. A short-term, vegan protein diet regimen nutritionally balanced in macronutrient composition compared to an omnivorous diet is hypothesized to improve metabolic measurements of blood sugar regulation, blood lipids, and amino acid metabolism.

METHODS AND RESULTS

This randomized, cross-over, controlled vegan versus animal diet challenge is conducted on 21 (11 female,10 male) healthy participants. Fasting plasma is measured during a 3 d diet intervention for clinical biochemistry and metabonomics. Intervention diet plans meet individual caloric needs. Meals are provided and supervised. Diet compliance is monitored.

CONCLUSIONS

The vegan diet lowers triglycerides, insulin and homeostatic model assessment (HOMA-IR), bile acids, elevated magnesium levels, and changed branched-chain amino acids (BCAAs) metabolism (p < 0.05), potentiating insulin and blood sugar control after 48 h. Cholesterol control improves significantly in the vegan versus omnivorous diets. Plasma amino acid and magnesium concentrations positively correlate with dietary amino acids. Polyunsaturated fatty acids and dietary fiber inversely correlate with insulin, HOMA-IR, and triglycerides. Nutritional biochemistries, BCAAs, insulin, and HOMA-IR are impacted by sexual dimorphism. A health-promoting, BCAA-associated metabolic signature is produced from a short-term, healthy, controlled, vegan diet challenge when compared with a healthy, controlled, omnivorous diet.

Proposed guidelines to evaluate scientific validity and evidence for genotype-based dietary advice

Nutrigenetic research examines the effects of inter-individual differences in genotype on responses to nutrients and other food components, in the context of health and of nutrient requirements. A practical application of nutrigenetics is the use of personal genetic information to guide recommendations for dietary choices that are more efficacious at the individual or genetic subgroup level relative to generic dietary advice. Nutrigenetics is unregulated, with no defined standards, beyond some commercially adopted codes of practice. Only a few official nutrition-related professional bodies have embraced the subject, and, consequently, there is a lack of educational resources or guidance for implementation of the outcomes of nutrigenetic research. To avoid misuse and to protect the public, personalised nutrigenetic advice and information should be based on clear evidence of validity grounded in a careful and defensible interpretation of outcomes from nutrigenetic research studies. Evidence requirements are clearly stated and assessed within the context of state-of-the-art 'evidence-based nutrition'. We have developed and present here a draft framework that can be used to assess the strength of the evidence for scientific validity of nutrigenetic knowledge and whether 'actionable'. In addition, we propose that this framework be used as the basis for developing transparent and scientifically sound advice to the public based on nutrigenetic tests. We feel that although this area is still in its infancy, minimal guidelines are required. Though these guidelines are based on semi-quantitative data, they should stimulate debate on their utility. This framework will be revised biennially, as knowledge on the subject increases.

Ancestors' dietary patterns and environments could drive positive selection in genes involved in micronutrient metabolism-the case of cofactor transporters

Background

During evolution, humans colonized different ecological niches and adopted a variety of subsistence strategies that gave rise to diverse selective pressures acting across the genome. Environmentally induced selection of vitamin, mineral, or other cofactor transporters could influence micronutrient-requiring molecular reactions and contribute to inter-individual variability in response to foods and nutritional interventions.

Methods

A comprehensive list of genes coding for transporters of cofactors or their precursors was built using data mining procedures from the HGDP dataset and then explored to detect evidence of positive genetic selection. This dataset was chosen since it comprises several genetically diverse worldwide populations whom ancestries have evolved in different environments and thus lived following various nutritional habits and lifestyles.

Results

We identified 312 cofactor transporter (CT) genes involved in between-cell or sub-cellular compartment distribution of 28 cofactors derived from dietary intake. Twenty-four SNPs distributed across 14 CT genes separated populations into continental and intra-continental groups such as African hunter-gatherers and farmers, and between Native American sub-populations. Notably, four SNPs were located in SLC24A3 with one being a known eQTL of the NCKX3 protein.

Conclusions

These findings could support the importance of considering individual’s genetic makeup along with their metabolic profile when tailoring personalized dietary interventions for optimizing health.

Electronic supplementary material

The online version of this article (10.1186/s12263-017-0579-x) contains supplementary material, which is available to authorized users.

Propelling the paradigm shift from reductionism to systems nutrition

The complex physiology of living organisms represents a challenge for mechanistic understanding of the action of dietary bioactives in the human body and of their possible role in health and disease. Animal, cell, and microbial models have been extensively used to address questions that could not be pursued experimentally in humans, posing an additional level of complexity in translation of the results to healthy and diseased metabolism. The past few decades have witnessed a surge in development of increasingly sensitive molecular techniques and bioinformatic tools for storing, managing, and analyzing increasingly large datasets. Application of such powerful means to molecular nutrition research led to a major leap in study designs and experimental approaches yielding experimental data connecting dietary components to human health. Scientific journals bear major responsibilities in the advancement of science. As primary actors of dissemination to the scientific community, journals can impose rigid criteria for publishing only sound, reliable, and reproducible data. Journal policies are meant to guide potential authors to adopt the most updated standardization guidelines and shared best practices. Such policies evolve in parallel with the evolution of novel approaches and emerging challenges and therefore require constant updating. We highlight in this manuscript the major scientific issues that led to formulating new, updated journal policies for Genes & Nutrition, a journal which targets the growing field of nutritional systems biology interfacing personalized nutrition and preventive medicine, with the ultimate goal of promoting health and preventing or treating disease. We focus here on relevant issues requiring standardization in nutrition research. We also introduce new sections on human genetic variation and nutritional bioinformatics which follow the evolution of nutritional science into the twenty-first century.

A network analysis of cofactor-protein interactions for analyzing associations between human nutrition and diseases

The involvement of vitamins and other micronutrients in intermediary metabolism was elucidated in the mid 1900's at the level of individual biochemical reactions. Biochemical pathways remain the foundational knowledgebase for understanding how micronutrient adequacy modulates health in all life stages. Current daily recommended intakes were usually established on the basis of the association of a single nutrient to a single, most sensitive adverse effect and thus neglect interdependent and pleiotropic effects of micronutrients on biological systems. Hence, the understanding of the impact of overt or sub-clinical nutrient deficiencies on biological processes remains incomplete. Developing a more complete view of the role of micronutrients and their metabolic products in protein-mediated reactions is of importance. We thus integrated and represented cofactor-protein interaction data from multiple and diverse sources into a multi-layer network representation that links cofactors, cofactor-interacting proteins, biological processes, and diseases. Network representation of this information is a key feature of the present analysis and enables the integration of data from individual biochemical reactions and protein-protein interactions into a systems view, which may guide strategies for targeted nutritional interventions aimed at improving health and preventing diseases.

Systems-Level Nutrition Approaches to Define Phenotypes Resulting from Complex Gene-Environment Interactions

High-throughput metabolomic, proteomic, and genomic technologies have delivered 21st-century data showing that humans cannot be randomized into groups: individuals are genetically and biochemically distinct. Gene-environment interactions caused by unique dietary and lifestyle factors contribute to the heterogeneity in physiologies observed in human studies. The risk factors determined for populations (i.e. the population-attributable risk) cannot be applied to the individual. Developing individual risk/benefit factors in light of the genetic diversity of human populations, the complexity of foods, culture and lifestyle, and the variety in metabolic processes that lead to health or disease are significant challenges for personalizing dietary advice for healthy or diseased individuals.

The genomics of micronutrient requirements

Healthy nutrition is accepted as a cornerstone of public health strategies for reducing the risk of noncommunicable conditions such as obesity, cardiovascular disease, and related morbidities. However, many research studies continue to focus on single or at most a few factors that may elicit a metabolic effect. These reductionist approaches resulted in: (1) exaggerated claims for nutrition as a cure or prevention of disease; (2) the wide use of empirically based dietary regimens, as if one fits all; and (3) frequent disappointment of consumers, patients, and healthcare providers about the real impact nutrition can make on medicine and health. Multiple factors including environment, host and microbiome genetics, social context, the chemical form of the nutrient, its (bio)availability, and chemical and metabolic interactions among nutrients all interact to result in nutrient requirement and in health outcomes. Advances in laboratory methodologies, especially in analytical and separation techniques, are making the chemical dissection of foods and their availability in physiological tissues possible in an unprecedented manner. These omics technologies have opened opportunities for extending knowledge of micronutrients and of their metabolic and endocrine roles. While these technologies are crucial, more holistic approaches to the analysis of physiology and environment, novel experimental designs, and more sophisticated computational methods are needed to advance our understanding of how nutrition influences health of individuals.

Metabolic fate of fructose in human adipocytes: a targeted 13C tracer fate association study

The development of obesity is becoming an international problem and the role of fructose is unclear. Studies using liver tissue and hepatocytes have contributed to the understanding of fructose metabolism. Excess fructose consumption also affects extra hepatic tissues including adipose tissue. The effects of fructose on human adipocytes are not yet fully characterized, although in vivo studies have noted increased adiposity and weight gain in response to fructose sweetened-beverages. In order to understand and predict the metabolic responses of adipocytes to fructose, this study examined differentiating and differentiated human adipocytes in culture, exposed to a range of fructose concentrations equivalent to that reported in blood after consuming fructose. A stable isotope based dynamic profiling method using [U-¹³C₆]-d-fructose tracer was used to examine the metabolism and fate of fructose. A targeted stable isotope tracer fate association method was used to analyze metabolic fluxes and flux surrogates with exposure to escalating fructose concentration. This study demonstrated that fructose stimulates anabolic processes in adipocytes robustly, including glutamate and de novo fatty acid synthesis. Furthermore, fructose also augments the release of free palmitate from fully differentiated adipocytes. These results imply that in the presence of fructose, the metabolic response of adipocytes in culture is altered in a dose dependent manner, particularly favoring increased glutamate and fatty acid synthesis and release, warranting further in vivo studies.

Translational genomics

The term "Translational Genomics" reflects both title and mission of this new journal. "Translational" has traditionally been understood as "applied research" or "development", different from or even opposed to "basic research". Recent scientific and societal developments have triggered a re-assessment of the connotation that "translational" and "basic" are either/or activities: translational research nowadays aims at feeding the best science into applications and solutions for human society. We therefore argue here basic science to be challenged and leveraged for its relevance to human health and societal benefits. This more recent approach and attitude are catalyzed by four trends or developments: evidence-based solutions; large-scale, high dimensional data; consumer/patient empowerment; and systems-level understanding.

B vitamin polymorphisms and behavior: evidence of associations with neurodevelopment, depression, schizophrenia, bipolar disorder and cognitive decline

The B vitamins folic acid, vitamin B12 and B6 are essential for neuronal function, and severe deficiencies have been linked to increased risk of neurodevelopmental disorders, psychiatric disease and dementia. Polymorphisms of genes involved in B vitamin absorption, metabolism and function, such as methylene tetrahydrofolate reductase (MTHFR), cystathionine β synthase (CβS), transcobalamin 2 receptor (TCN2) and methionine synthase reductase (MTRR), have also been linked to increased incidence of psychiatric and cognitive disorders. However, the effects of these polymorphisms are often quite small and many studies failed to show any meaningful or consistent associations. This review discusses previous findings from clinical studies and highlights gaps in knowledge. Future studies assessing B vitamin-associated polymorphisms must take into account not just traditional demographics, but subjects' overall diet, relevant biomarkers of nutritional status and also analyze related genetic factors that may exacerbate behavioral effects or nutritional status.

Genetic associations with micronutrient levels identified in immune and gastrointestinal networks

The discovery of vitamins and clarification of their role in preventing frank essential nutrient deficiencies occurred in the early 1900s. Much vitamin research has understandably focused on public health and the effects of single nutrients to alleviate acute conditions. The physiological processes for maintaining health, however, are complex systems that depend upon interactions between multiple nutrients, environmental factors, and genetic makeup. To analyze the relationship between these factors and nutritional health, data were obtained from an observational, community-based participatory research program of children and teens (age 6–14) enrolled in a summer day camp in the Delta region of Arkansas. Assessments of erythrocyte S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH), plasma homocysteine (Hcy) and 6 organic micronutrients (retinol, 25-hydroxy vitamin D3, pyridoxal, thiamin, riboflavin, and vitamin E), and 1,129 plasma proteins were performed at 3 time points in each of 2 years. Genetic makeup was analyzed with 1 M SNP genotyping arrays, and nutrient status was assessed with 24-h dietary intake questionnaires. A pattern of metabolites (met_PC1) that included the ratio of erythrocyte SAM/SAH, Hcy, and 5 vitamins were identified by principal component analysis. Met_PC1 levels were significantly associated with (1) single-nucleotide polymorphisms, (2) levels of plasma proteins, and (3) multilocus genotypes coding for gastrointestinal and immune functions, as identified in a global network of metabolic/protein–protein interactions. Subsequent mining of data from curated pathway, network, and genome-wide association studies identified genetic and functional relationships that may be explained by gene–nutrient interactions. The systems nutrition strategy described here has thus associated a multivariate metabolite pattern in blood with genes involved in immune and gastrointestinal functions.

Methylation potential associated with diet, genotype, protein, and metabolite levels in the Delta Obesity Vitamin Study

Micronutrient research typically focuses on analyzing the effects of single or a few nutrients on health by analyzing a limited number of biomarkers. The observational study described here analyzed micronutrients, plasma proteins, dietary intakes, and genotype using a systems approach. Participants attended a community-based summer day program for 6-14 year old in 2 years. Genetic makeup, blood metabolite and protein levels, and dietary differences were measured in each individual. Twenty-four-hour dietary intakes, eight micronutrients (vitamins A, D, E, thiamin, folic acid, riboflavin, pyridoxal, and pyridoxine) and 3 one-carbon metabolites [homocysteine (Hcy), S-adenosylmethionine (SAM), and S-adenosylhomocysteine (SAH)], and 1,129 plasma proteins were analyzed as a function of diet at metabolite level, plasma protein level, age, and sex. Cluster analysis identified two groups differing in SAM/SAH and differing in dietary intake patterns indicating that SAM/SAH was a potential marker of nutritional status. The approach used to analyze genetic association with the SAM/SAH metabolites is called middle-out: SNPs in 275 genes involved in the one-carbon pathway (folate, pyridoxal/pyridoxine, thiamin) or were correlated with SAM/SAH (vitamin A, E, Hcy) were analyzed instead of the entire 1M SNP data set. This procedure identified 46 SNPs in 25 genes associated with SAM/SAH demonstrating a genetic contribution to the methylation potential. Individual plasma metabolites correlated with 99 plasma proteins. Fourteen proteins correlated with body mass index, 49 with group age, and 30 with sex. The analytical strategy described here identified subgroups for targeted nutritional interventions.

Consensus statement understanding health and malnutrition through a systems approach: the ENOUGH program for early life

Nutrition research, like most biomedical disciplines, adopted and often uses experimental approaches based on Beadle and Tatum's one gene-one polypeptide hypothesis, thereby reducing biological processes to single reactions or pathways. Systems thinking is needed to understand the complexity of health and disease processes requiring measurements of physiological processes, as well as environmental and social factors, which may alter the expression of genetic information. Analysis of physiological processes with omics technologies to assess systems' responses has only become available over the past decade and remains costly. Studies of environmental and social conditions known to alter health are often not connected to biomedical research. While these facts are widely accepted, developing and conducting comprehensive research programs for health are often beyond financial and human resources of single research groups. We propose a new research program on essential nutrients for optimal underpinning of growth and health (ENOUGH) that will use systems approaches with more comprehensive measurements and biostatistical analysis of the many biological and environmental factors that influence undernutrition. Creating a knowledge base for nutrition and health is a necessary first step toward developing solutions targeted to different populations in diverse social and physical environments for the two billion undernourished people in developed and developing economies.

Perspective: a systems approach to diabetes research

We review here the status of human type 2 diabetes studies from a genetic, epidemiological, and clinical (intervention) perspective. Most studies limit analyses to one or a few omic technologies providing data of components of physiological processes. Since all chronic diseases are multifactorial and arise from complex interactions between genetic makeup and environment, type 2 diabetes mellitus (T2DM) is a collection of sub-phenotypes resulting in high fasting glucose. The underlying gene–environment interactions that produce these classes of T2DM are imperfectly characterized. Based on assessments of the complexity of T2DM, we propose a systems biology approach to advance the understanding of origin, onset, development, prevention, and treatment of this complex disease. This systems-based strategy is based on new study design principles and the integrated application of omics technologies: we pursue longitudinal studies in which each subject is analyzed at both homeostasis and after (healthy and safe) challenges. Each enrolled subject functions thereby as their own case and control and this design avoids assigning the subjects a priori to case and control groups based on limited phenotyping. Analyses at different time points along this longitudinal investigation are performed with a comprehensive set of omics platforms. These data sets are generated in a biological context, rather than biochemical compound class-driven manner, which we term “systems omics.”

Discovery-based nutritional systems biology: developing N-of-1 nutrigenomic research

The progress in and success of biomedical research over the past century was built on the foundation outlined in R.A. Fisher's The Design of Experiments (1935), which described the theory and methodological approach to designing research studies. A key tenet of Fisher's treatise, widely adopted by the research community, is randomization, the process of assigning individuals to random groups or treatments. Comparing outcomes or responses between these groups yields “risk factors” called population attributable risks (PAR), which are statistical estimates of the percentage reduction in disease if the risk were avoided or in the case of genetic associations, if the gene variant were not present in the population .High throughput metabolomics, proteomic and genomic technologies provide 21st century data that humans cannot be randomized into groups: individuals are genetically and biochemically distinct. Gene–environment interactions caused by unique dietary and lifestyle factors contribute to heterogeneity in physiologies observed in human studies. The risk factors determined for populations (i.e., PAR) cannot be applied to the individual. Developing individual risk or benefit factors in light of the genetic diversity of human populations, the complexity of foods, culture and lifestyle, and the variety of metabolic processes that lead to health or disease are significant challenges for personalizing dietary advice for healthy or medical treatments for individuals with chronic disease.

Gene expression variability in human hepatic drug metabolizing enzymes and transporters

Interindividual variability in the expression of drug-metabolizing enzymes and transporters (DMETs) in human liver may contribute to interindividual differences in drug efficacy and adverse reactions. Published studies that analyzed variability in the expression of DMET genes were limited by sample sizes and the number of genes profiled. We systematically analyzed the expression of 374 DMETs from a microarray data set consisting of gene expression profiles derived from 427 human liver samples. The standard deviation of interindividual expression for DMET genes was much higher than that for non-DMET genes. The 20 DMET genes with the largest variability in the expression provided examples of the interindividual variation. Gene expression data were also analyzed using network analysis methods, which delineates the similarities of biological functionalities and regulation mechanisms for these highly variable DMET genes. Expression variability of human hepatic DMET genes may affect drug-gene interactions and disease susceptibility, with concomitant clinical implications.

Human Variome Project country nodes: documenting genetic information within a country

The Human Variome Project (http://www.humanvariomeproject.org) is an international effort aiming to systematically collect and share information on all human genetic variation. The two main pillars of this effort are gene/disease-specific databases and a network of Human Variome Project Country Nodes. The latter are nationwide efforts to document the genomic variation reported within a specific population. The development and successful operation of the Human Variome Project Country Nodes are of utmost importance to the success of Human Variome Project's aims and goals because they not only allow the genetic burden of disease to be quantified in different countries, but also provide diagnosticians and researchers access to an up-to-date resource that will assist them in their daily clinical practice and biomedical research, respectively. Here, we report the discussions and recommendations that resulted from the inaugural meeting of the International Confederation of Countries Advisory Council, held on 12th December 2011, during the 2011 Human Variome Project Beijing Meeting. We discuss the steps necessary to maximize the impact of the Country Node effort for developing regional and country-specific clinical genetics resources and summarize a few well-coordinated genetic data collection initiatives that would serve as paradigms for similar projects.

Assessment of research models for testing gene-environment interactions

Throughout the last century, possible effects of exposure to toxicants, nutrients or drugs were examined primarily by studies of groups or populations. Individual variation in responses was acknowledged but could not be analyzed due to lack of information or tools to analyze individual genetic make-ups and lifestyle factors such as diet and activity. The Human Genome, Haplotype Map, 1000Genomes, and Human Variome Projects are identifying and cataloging the variation found within humans. Advances in DNA sequencing technologies will soon permit the characterization of individual genomes in clinical and basic research studies, thus allowing associations to be made between an individual genotype and the response to a particular exposure. Such knowledge and tools have generated a significant challenge for scientists: to design and conduct research studies that account for individual genetic variation. However, before these studies are done in humans, they will be performed in various in vivo and in vitro models. The advantages and disadvantages of some of the model test systems that are being used or developed in relation to individual genetic make-up and responses to xenobiotics are discussed.

How to catch all those mutations--the report of the third Human Variome Project Meeting, UNESCO Paris, May 2010

The third Human Variome Project (HVP) Meeting "Integration and Implementation" was held under UNESCO Patronage in Paris, France, at the UNESCO Headquarters May 10-14, 2010. The major aims of the HVP are the collection, curation, and distribution of all human genetic variation affecting health. The HVP has drawn together disparate groups, by country, gene of interest, and expertise, who are working for the common good with the shared goal of pushing the boundaries of the human variome and collaborating to avoid unnecessary duplication. The meeting addressed the 12 key areas that form the current framework of HVP activities: Ethics; Nomenclature and Standards; Publication, Credit and Incentives; Data Collection from Clinics; Overall Data Integration and Access-Peripheral Systems/Software; Data Collection from Laboratories; Assessment of Pathogenicity; Country Specific Collection; Translation to Healthcare and Personalized Medicine; Data Transfer, Databasing, and Curation; Overall Data Integration and Access-Central Systems; and Funding Mechanisms and Sustainability. In addition, three societies that support the goals and the mission of HVP also held their own Workshops with the view to advance disease-specific variation data collection and utilization: the International Society for Gastrointestinal Hereditary Tumours, the Micronutrient Genomics Project, and the Neurogenetics Consortium.

Similarities and differences in the expression of drug-metabolizing enzymes between human hepatic cell lines and primary human hepatocytes

In addition to primary human hepatocytes, hepatoma cell lines, and transfected nonhepatoma, hepatic cell lines have been used for pharmacological and toxicological studies. However, a systematic evaluation and a general report of the gene expression spectra of drug-metabolizing enzymes and transporters (DMETs) in these in vitro systems are not currently available. To fill this information gap and to provide references for future studies, we systematically characterized the basal gene expression profiles of 251 drug-metabolizing enzymes in untreated primary human hepatocytes from six donors, four commonly used hepatoma cell lines (HepG2, Huh7, SK-Hep-1, and Hep3B), and one transfected human liver epithelial cell line. A large variation in DMET expression spectra was observed between hepatic cell lines and primary hepatocytes, with the complete absence or much lower abundance of certain DMETs in hepatic cell lines. Furthermore, the basal DMET expression spectra of five hepatic cell lines are summarized, providing references for researchers to choose carefully appropriate in vitro models for their studies of drug metabolism and toxicity, especially for studies with drugs in which toxicities are mediated through the formation of reactive metabolites.

Carbohydrate metabolic pathway genes associated with quantitative trait loci (QTL) for obesity and type 2 diabetes: identification by data mining

Increasing consumption of refined carbohydrates is now being recognized as a primary contributor to the development of nutritionally related chronic diseases such as obesity and type 2 diabetes mellitus (T2DM). A data mining approach was used to evaluate the role of carbohydrate metabolic pathway genes in the development of obesity and T2DM. Data from public databases were used to map the position of the carbohydrate metabolic pathway genes to known quantitative trait loci (QTL) for obesity and T2DM and for examining the pathway genes for the presence of sequence and structural genetic variants such as single nucleotide polymorphisms (SNPs) and copy number variants (CNS), respectively. The results demonstrated that a majority of the genes of the carbohydrate metabolic pathways are associated with QTL for obesity and many for T2DM. In addition, some key genes of the pathways also encode non-synonymous SNPs that exhibit significant differences in population frequencies. This study emphasizes the significance of the metabolic pathways genes in the development of disease phenotypes, its differential occurrence across populations and between individuals, and a strategy for interpreting an individuals' risk for disease.

Connecting the Human Variome Project to nutrigenomics

Nutrigenomics is the science of analyzing and understanding gene-nutrient interactions, which because of the genetic heterogeneity, varying degrees of interaction among gene products, and the environmental diversity is a complex science. Although much knowledge of human diversity has been accumulated, estimates suggest that ~90% of genetic variation has not yet been characterized. Identification of the DNA sequence variants that contribute to nutrition-related disease risk is essential for developing a better understanding of the complex causes of disease in humans, including nutrition-related disease. The Human Variome Project (HVP; http://www.humanvariomeproject.org/) is an international effort to systematically identify genes, their mutations, and their variants associated with phenotypic variability and indications of human disease or phenotype. Since nutrigenomic research uses genetic information in the design and analysis of experiments, the HVP is an essential collaborator for ongoing studies of gene-nutrient interactions. With the advent of next generation sequencing methodologies and the understanding of the undiscovered variation in human genomes, the nutrigenomic community will be generating novel sequence data and results. The guidelines and practices of the HVP can guide and harmonize these efforts.

Web-enabled and improved software tools and data are needed to measure nutrient intakes and physical activity for personalized health research

Food intake, physical activity (PA), and genetic makeup each affect health and each factor influences the impact of the other 2 factors. Nutrigenomics describes interactions between genes and environment. Knowledge about the interplay between environment and genetics would be improved if experimental designs included measures of nutrient intake and PA. Lack of familiarity about how to analyze environmental variables and ease of access to tools and measurement instruments are 2 deterrents to these combined studies. This article describes the state of the art for measuring food intake and PA to encourage researchers to make their tools better known and more available to workers in other fields. Information presented was discussed during a workshop on this topic sponsored by the USDA, NIH, and FDA in the spring of 2009.

The Micronutrient Genomics Project: a community-driven knowledge base for micronutrient research

Micronutrients influence multiple metabolic pathways including oxidative and inflammatory processes. Optimum micronutrient supply is important for the maintenance of homeostasis in metabolism and, ultimately, for maintaining good health. With advances in systems biology and genomics technologies, it is becoming feasible to assess the activity of single and multiple micronutrients in their complete biological context. Existing research collects fragments of information, which are not stored systematically and are thus not optimally disseminated. The Micronutrient Genomics Project (MGP) was established as a community-driven project to facilitate the development of systematic capture, storage, management, analyses, and dissemination of data and knowledge generated by biological studies focused on micronutrient–genome interactions. Specifically, the MGP creates a public portal and open-source bioinformatics toolbox for all “omics” information and evaluation of micronutrient and health studies. The core of the project focuses on access to, and visualization of, genetic/genomic, transcriptomic, proteomic and metabolomic information related to micronutrients. For each micronutrient, an expert group is or will be established combining the various relevant areas (including genetics, nutrition, biochemistry, and epidemiology). Each expert group will (1) collect all available knowledge, (2) collaborate with bioinformatics teams towards constructing the pathways and biological networks, and (3) publish their findings on a regular basis. The project is coordinated in a transparent manner, regular meetings are organized and dissemination is arranged through tools, a toolbox web portal, a communications website and dedicated publications.

Two new ArrayTrack libraries for personalized biomedical research

Background

Recent advances in high-throughput genotyping technology are paving the way for research in personalized medicine and nutrition. However, most of the genetic markers identified from association studies account for a small contribution to the total risk/benefit of the studied phenotypic trait. Testing whether the candidate genes identified by association studies are causal is critically important to the development of personalized medicine and nutrition. An efficient data mining strategy and a set of sophisticated tools are necessary to help better understand and utilize the findings from genetic association studies.

Description

SNP (single nucleotide polymorphism) and QTL (quantitative trait locus) libraries were constructed and incorporated into ArrayTrack, with user-friendly interfaces and powerful search features. Data from several public repositories were collected in the SNP and QTL libraries and connected to other domain libraries (genes, proteins, metabolites, and pathways) in ArrayTrack. Linking the data sets within ArrayTrack allows searching of SNP and QTL data as well as their relationships to other biological molecules. The SNP library includes approximately 15 million human SNPs and their annotations, while the QTL library contains publically available QTLs identified in mouse, rat, and human. The QTL library was developed for finding the overlap between the map position of a candidate or metabolic gene and QTLs from these species. Two use cases were included to demonstrate the utility of these tools. The SNP and QTL libraries are freely available to the public through ArrayTrack at http://www.fda.gov/ArrayTrack.

Conclusions

These libraries developed in ArrayTrack contain comprehensive information on SNPs and QTLs and are further cross-linked to other libraries. Connecting domain specific knowledge is a cornerstone of systems biology strategies and allows for a better understanding of the genetic and biological context of the findings from genetic association studies.

Assessment of dietary intake: NuGO symposium report

Advances in genomics science and associated bioinformatics and technology mean that excellent tools are available for characterising human genotypes. At the same time, approaches for characterising individual phenotypes are developing rapidly. In contrast, there has been much less investment in novel methodology for measuring dietary exposures so that there is now a significant gap in the toolkit for those investigating how diet interacts with genotype to determine phenotype. This symposium reviewed the strengths and limitations of current tools used in assessment of dietary intake and the potential to improve these tools through, for example, the use of statistical techniques that combine information from different sources (such as modelling and calibration methods) to ameliorate measurement error and to provide validity checks. Speakers examined the use of approaches based on technologies such as mobile ‘phones, digital cameras and Web-based systems which offer the potential for more acceptable (for study participants) and less laborious (for researchers and participants) routes to more robust data collection. In addition, the application of omics, especially metabolomics, tools to biofluids to identify new biomarkers of intake offers great potential to provide objective measures of food consumption with the advantage that data may be collected in forms that can be integrated readily with other high throughput (nutrigenomic) technologies.

Challenges of molecular nutrition research 6: the nutritional phenotype database to store, share and evaluate nutritional systems biology studies

The challenge of modern nutrition and health research is to identify food-based strategies promoting life-long optimal health and well-being. This research is complex because it exploits a multitude of bioactive compounds acting on an extensive network of interacting processes. Whereas nutrition research can profit enormously from the revolution in ‘omics’ technologies, it has discipline-specific requirements for analytical and bioinformatic procedures. In addition to measurements of the parameters of interest (measures of health), extensive description of the subjects of study and foods or diets consumed is central for describing the nutritional phenotype. We propose and pursue an infrastructural activity of constructing the “Nutritional Phenotype database” (dbNP). When fully developed, dbNP will be a research and collaboration tool and a publicly available data and knowledge repository. Creation and implementation of the dbNP will maximize benefits to the research community by enabling integration and interrogation of data from multiple studies, from different research groups, different countries and different—omics levels. The dbNP is designed to facilitate storage of biologically relevant, pre-processed—omics data, as well as study descriptive and study participant phenotype data. It is also important to enable the combination of this information at different levels (e.g. to facilitate linkage of data describing participant phenotype, genotype and food intake with information on study design and—omics measurements, and to combine all of this with existing knowledge). The biological information stored in the database (i.e. genetics, transcriptomics, proteomics, biomarkers, metabolomics, functional assays, food intake and food composition) is tailored to nutrition research and embedded in an environment of standard procedures and protocols, annotations, modular data-basing, networking and integrated bioinformatics. The dbNP is an evolving enterprise, which is only sustainable if it is accepted and adopted by the wider nutrition and health research community as an open source, pre-competitive and publicly available resource where many partners both can contribute and profit from its developments. We introduce the Nutrigenomics Organisation (NuGO, http://www.nugo.org) as a membership association responsible for establishing and curating the dbNP. Within NuGO, all efforts related to dbNP (i.e. usage, coordination, integration, facilitation and maintenance) will be directed towards a sustainable and federated infrastructure.